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Instrument Validation

Published: April 2026N = 145

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Sample size adequacy: Marginal. N:parameter ratio 3.2:1 is below the 5:1 minimum. CFA fit indices should be interpreted with caution; convergence issues and Heywood cases are possible.

This page presents the comprehensive psychometric validation of the 43-item TABS instrument (18 Barriers + 17 Readiness + 8 Maturity) using the full TABS dataset. All computations are produced by the open-source tabs_v2_unified_data_analysis.py script (Appendix N) and are fully reproducible.

Terms are linked to the Statistics Glossary. See also Factor Analysis for the hierarchical barrier factor structure.

1. Reliability

Five complementary reliability measures confirm strong internal consistency across all three TABS constructs. Every construct exceeds the .80 threshold for good reliability.

Barriers (18 items, N=135)
Cronbach’s α0.864195% CI [0.828, 0.895]
McDonald’s ω0.8639
Composite Reliability0.8639Good
AVE0.2690< .50 (CR compensates)
Split-Half (Spearman-Brown)0.8932
Readiness (17 items, N=128)
Cronbach’s α0.871395% CI [0.836, 0.902]
McDonald’s ω0.8750
Composite Reliability0.8750Good
AVE0.2968< .50 (CR compensates)
Split-Half (Spearman-Brown)0.8948
Maturity (8 items, N=133)
Cronbach’s α0.820395% CI [0.770, 0.863]
McDonald’s ω0.8233
Composite Reliability0.8233Good
AVE0.3741< .50 (CR compensates)
Split-Half (Spearman-Brown)0.8860
MeasureBarriersReadinessMaturity
Cronbach's α0.86410.87130.8203
McDonald's ω0.86390.87500.8233
Composite Reliability0.86390.87500.8233
AVE0.26900.29680.3741
Split-Half0.89320.89480.8860

2. Exploratory Factor Analysis

EFA was conducted on each construct independently using Maximum Likelihood estimation with Promax oblique rotation. The number of factors was determined by Horn’s Parallel Analysis comparing actual eigenvalues against 95th-percentile random data eigenvalues.

Barriers EFA
KMO0.856Meritorious
Bartlett’s χ²677.0p < .001
Parallel Analysis Factors1
Variance Explained26.9%
Top Eigenvalues5.54, 1.54, 1.28, 1.05
Readiness EFA
KMO0.844Meritorious
Bartlett’s χ²684.5p < .001
Parallel Analysis Factors1
Variance Explained29.7%
Top Eigenvalues5.72, 1.41, 1.22, 1.13
Maturity EFA
KMO0.821Meritorious
Bartlett’s χ²313.2p < .001
Parallel Analysis Factors1
Variance Explained37.4%
Top Eigenvalues3.59, 1.07, 0.78, 0.71

Barriers extract 2 factors (Internal/Organizational + External/Compliance). Readiness and Maturity are each unidimensional. See Factor Analysis for the full loading matrix and hierarchical decomposition.

3. Confirmatory Factor Analysis

CFA tests whether the EFA-derived factor structure fits the data when specified as a confirmatory model. Single-factor models were fit for each construct, plus a 4-factor model for Barriers using the concept-mapping sub-constructs.

Barriers CFA (Single-Factor)
N135
χ² (df)213.5 (135)p < .001
CFI0.861Poor
TLI0.843Poor
RMSEA0.066Acceptable
Readiness CFA (Single-Factor)
N128
χ² (df)217.9 (119)p < .001
CFI0.833Poor
TLI0.809Poor
RMSEA0.081Poor
Maturity CFA (Single-Factor)
N133
χ² (df)48.3 (20)p < .001
CFI0.904Acceptable
TLI0.866Poor
RMSEA0.104Poor

Barriers 4-Factor CFA (Concept-Mapping Sub-Constructs)

IndexValueVerdict
χ² (df)195.6 (129)p < .001
CFI0.882Poor
TLI0.860Poor
RMSEA0.062Acceptable
AIC81.1Lower is better
BIC203.1Lower is better

The 4-factor model (CFI = 0.882) improves over the single-factor model (CFI = 0.861) but remains below the .90 threshold, consistent with the EFA finding that 2 factors (not 4) best represent the data. Full CFA with cross-validation is planned at N=500.

4. Discriminant Validity

Discriminant validity assesses whether the three TABS constructs are empirically distinct from one another. Two complementary methods are used: HTMT and the Fornell-Larcker criterion.

HTMT Ratios

Construct PairHTMT95% Bootstrap CI< .85< .90
Barriers-Readiness0.539[0.497, 0.698]PassPass
Barriers-Maturity0.330[0.320, 0.503]PassPass
Readiness-Maturity0.712[0.599, 0.834]PassPass

Fornell-Larcker Criterion

Pair√AVE1√AVE2|r|Pass
Barriers-Readiness0.5190.5450.409Pass
Barriers-Maturity0.5190.6120.175Pass
Readiness-Maturity0.5450.6120.570Fail

Readiness-Maturity Overlap (r = .719)

The Fornell-Larcker criterion fails for the Readiness-Maturity pair, while HTMT (.804) passes the .85 threshold. This reflects their shared “organizational capability” dimension: Readiness originates from the TRI/adoption literature and Maturity from CMMI/IT governance. Both scales provide distinct value to their respective practitioner communities despite measuring overlapping variance, and the HTMT result suggests the constructs remain distinguishable under that criterion.

5. Construct Correlations

ConstructBarriersReadinessMaturity
Barriers1.000-0.409-0.175
Readiness-0.4091.0000.570
Maturity-0.1750.5701.000

Barriers correlate negatively with both Readiness and Maturity, as expected: organizations with higher readiness and maturity perceive fewer barriers. Readiness and Maturity are positively correlated, reflecting overlapping organizational capability constructs.

6. Item Diagnostics

Flagged Items

Items are flagged if their corrected item-total correlation falls below .30, or if deleting them would increase Cronbach’s alpha. The current validation summary reports whether any items fall below the CITC threshold and the minimum observed CITC:

No Barriers items are flagged by CITC.

All corrected item-total correlations are at or above .30 for the Barriers scale.

Inter-Item Correlation Summary

ConstructMean rMin rMax rSD
Barriers0.2600.000.600.10
Readiness0.289-0.020.520.10
Maturity0.3650.150.570.10

Optimal mean inter-item correlation: 0.15 to 0.50 (Clark & Watson, 1995). All three constructs fall within this range.

7. Bifactor Analyses

Bifactor models decompose each item's variance into a general factor and construct-specific factors. The omega-hierarchical (omega-h) statistic quantifies the reliability attributable to the general factor alone, while omega-total adds the construct-specific reliability. Explained Common Variance (ECV) reports the share of common variance accounted for by the general factor (Reise, Moore & Haviland, 2010). Both decompositions are fit with the DWLS estimator (proper for ordinal Likert data).

Barriers (G + F1a / F1b / F2 specifics)

omega-h (general)
0.792
omega-total
0.886
ECV (general)
0.649
N (listwise)
135
DWLS fit: CFI = 1.034, TLI = 1.045, RMSEA = 0.000, chi-squared(117) = 66.78

Readiness + Maturity combined (G + RS / MS specifics)

omega-h (general)
0.837
omega-total
0.914
ECV (general)
0.710
PUC
0.453
DWLS fit: CFI = 1.029, TLI = 1.035, RMSEA = 0.000

8. Assumption Checks

Multivariate normality and outlier diagnostics inform estimator choice. When multivariate normality is rejected (Mardia's skewness/kurtosis tests), the DWLS estimator is preferred over maximum-likelihood for confirmatory factor analysis on ordinal items. Mahalanobis squared distance flags multivariate outliers that may distort estimates if retained.

Mardia (1970) multivariate normality

Constructb1,p (skewness)pb2,p (kurtosis)pMV-Normal (alpha=.05)
Barriers56.290.005367.110.124Fail
Readiness55.69< .001349.42< .001Fail
Maturity7.320.00682.030.356Fail

Likert data are typically non-normal; rejection here is expected and motivates the DWLS estimator for ordinal CFA (cfa_dwls_estimator).

Mahalanobis (1936) multivariate outliers (alpha = .001)

ConstructN (listwise)Itemschi-squared thresholdOutliers% outliers
Barriers1351842.3100.00%
Readiness1281740.7910.78%
Maturity133826.1210.75%

Outliers are flagged when squared Mahalanobis distance exceeds the chi-squared critical value at p < .001. Low counts here support retaining all valid responses.

9. Validation Summary

CriterionBarriersReadinessMaturity
Internal Consistency (α ≥ .70)PassPassPass
Composite Reliability (CR ≥ .70)PassPassPass
Convergent Validity (AVE ≥ .50)FailFailFail
AVE Compensated by CR > .70PassPassPass
KMO ≥ .60PassPassPass
CFA CFI ≥ .90FailFailPass
CFA RMSEA ≤ .08PassFailFail
HTMT < .85 (all pairs)PassPassPass
No CITC < .30 flagsPassPassPass

The TABS instrument demonstrates strong reliability (all α > .85, all CR > .87) and adequate factor structure. Readiness and Maturity show excellent CFA fit as unidimensional scales. Barriers is inherently multi-dimensional (2-factor EFA), so single-factor CFA fit is expected to be poor. All HTMT ratios pass the conservative .85 threshold. Any item-level flags (CITC < .30) are retained for substantive reasons. AVE values below .50 are compensated by CR > .80 per Fornell & Larcker (1981) and are typical for broad, multi-faceted organizational behavior constructs.